Résumé :
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[BDSP. Notice produite par INIST 9sjR0xgb. Diffusion soumise à autorisation]. Background Capture-recapture (CR) methods are increasingly used to estimate the size of human populations, including those with diabetes. Few studies have examined the demographic details needed to match patients on the lists used in these techniques, or to determine the optimum number of lists. Methods Six lists of known diabetic patients attending different medical settings during the study year were obtained. The effects on total enumeration after aggregation of these lists were examined using increasing numbers of demographic data items as patient identifiers. The CR estimates of prevalence were obtained using 15 different combinations of two lists. Estimates were obtained alter log-linear modelling for interdependence between different combinations of three and four lists, and after combining the six available lists into three logical lists. Results For matching patients, adding date of birth to first name and family name as matching criteria increased the total of identified patients from 2500 to 2585 (3% increase), corresponding to a period prevalence of 1.5% (95% CI : 1.41-1.52). Addition of further identifiers, such as partial postcode, only increased the estimate by a further 15 patients (0.5%), and more detailed matching with full postcode introduced uncertainty. The use of two-list CR yielded widely varying estimates of the total diabetic population from 1379 (95% CI : 435-2273) to 9554 (95% CI : 7291-10 983). (...)
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